scholarly journals An Online Reactive Power-Optimization Strategy Based on Load-Curve Prediction and Segmentation

2020 ◽  
Vol 10 (3) ◽  
pp. 1145
Author(s):  
Yaqiong Li ◽  
Tongxun Wang ◽  
Zhanfeng Deng
Keyword(s):  
Distribution Systems ◽  
Reactive Power ◽  
Power Optimization ◽  
Reactive Power Compensation ◽  
Optimization Strategy ◽  
Reactive Power Optimization ◽  
Load Curve ◽  
Effective Strategies ◽  
Network Losses ◽  
Compensation Device

Due to fluctuating characteristics of loads, dynamic reactive power optimization over a certain time period is essential to provide effective strategies to maintain the security and economic operation of distribution systems. In operation, reactive power compensation devices cannot be adjusted too frequently due to their lifetime constraints. Thus, in this paper, an online reactive power optimization strategy based on the segmentation of multiple predicted load curves is proposed to address this issue, aiming to minimize network losses and at the same time to minimize reactive power-compensation device adjustment times. Based on forecasted time series of loads, the strategy first segments each load curve into several sections by means of thresholding a filtered signal, and then optimizes reactive power dispatch based on average load in each section. Through case studies using a modified IEEE 34-bus system and field measurement of loads, the merits of the proposed strategy is verified in terms of both optimization performance and computational efficiency compared with state-of-the-art methods.

scholarly journals Reactive Power Optimization for Distribution Network Based on Distributed Random Gradient-Free Algorithm

Energies ◽  
2018 ◽  
Vol 11 (3) ◽  
pp. 534 ◽  
Author(s):  
Jun Xie ◽  
Chunxiang Liang ◽  
Yichen Xiao
Keyword(s):  
Distribution Systems ◽  
Reactive Power ◽  
Power Optimization ◽  
Distribution Network ◽  
Continuous Optimization ◽  
Distribution Networks ◽  
Optimal Operation ◽  
Centralized Control ◽  
Optimization Strategy ◽  
Reactive Power Optimization

The increasing penetration of distributed energy resources in distribution systems has brought a number of network management and operational challenges; reactive power variation has been identified as one of the dominant effects. Enormous growth in a variety of controllable devices that have complex control requirements are integrated in distribution networks. The operation modes of traditional centralized control are difficult to tackle these problems with central controller. When considering the non-linear multi-objective functions with discrete and continuous optimization variables, the proposed random gradient-free algorithm is employed to the optimal operation of controllable devices for reactive power optimization. This paper presents a distributed reactive power optimization algorithm that can obtain the global optimum solution based on random gradient-free algorithm for distribution network without requiring a central coordinator. By utilizing local measurements and local communications among capacitor banks and distributed generators (DGs), the proposed reactive power control strategy can realize the overall network voltage optimization and power loss minimization simultaneously. Simulation studies on the modified IEEE-69 bus distribution systems demonstrate the effectiveness and superiority of the proposed reactive power optimization strategy.

scholarly journals Multiobjective Reactive Power Optimization of Renewable Energy Power Plants Based on Time-and-Space Grouping Method

Energies ◽  
2020 ◽  
Vol 13 (14) ◽  
pp. 3556
Author(s):  
Linan Qu ◽  
Shujie Zhang ◽  
Hsiung-Cheng Lin ◽  
Ning Chen ◽  
Lingling Li
Keyword(s):  
Renewable Energy ◽  
Power Plants ◽  
Large Scale ◽  
Reactive Power ◽  
Power Optimization ◽  
Reactive Power Compensation ◽  
Mixed Integer ◽  
Reactive Power Optimization ◽  
Time And Space ◽  
Bus Voltage

The large-scale renewable energy power plants connected to a weak grid may cause bus voltage fluctuations in the renewable energy power plant and even power grid. Therefore, reactive power compensation is demanded to stabilize the bus voltage and reduce network loss. For this purpose, time-series characteristics of renewable energy power plants are firstly reflected using K-means++ clustering method. The time group behaviors of renewable energy power plants, spatial behaviors of renewable energy generation units, and a time-and-space grouping model of renewable energy power plants are thus established. Then, a mixed-integer optimization method for reactive power compensation in renewable energy power plants is developed based on the second-order cone programming (SOCP). Accordingly, power flow constraints can be simplified to achieve reactive power optimization more efficiently and quickly. Finally, the feasibility and economy for the proposed method are verified by actual renewable energy power plants.

scholarly journals Reactive power optimization strategy considering analytical impedance ratio

2017 ◽  
Author(s):  
Zhongchao Wu ◽  
Weibing Shen ◽  
Jinming Liu ◽  
Maoran Guo ◽  
Shoulin Zhang ◽  
...  
Keyword(s):  
Reactive Power ◽  
Power Optimization ◽  
Optimization Strategy ◽  
Reactive Power Optimization ◽  
Impedance Ratio

Application of Modified Artificial Fish Swarm Algorithm in Power System Reactive Power Optimization

2013 ◽  
Vol 321-324 ◽  
pp. 1361-1364
Author(s):  
Shu Kui Liu ◽  
Na Dong ◽  
Zhi Zheng ◽  
Li Cheng ◽  
Qi Li
Keyword(s):  
Power System ◽  
Optimization Algorithm ◽  
Reactive Power ◽  
Power Optimization ◽  
Reactive Power Optimization ◽  
Artificial Fish Swarm Algorithm ◽  
Comparison Results ◽  
Artificial Fish Swarm ◽  
Network Losses ◽  
Swarm Algorithm

Modified Artificial Fish Swarm Algorithm (MAFSA) based on the global search characteristic of Artificial Fish Swarm Algorithm (AFSA), and combined with the local search of chao optimization algorithm(COA), can avoid trapping into local minimal value and decrease the iteration numbers, which was a swarm intelligence optimization algorithm applied to continuous space. MAFSA was proposed to optimize the reactive power optimization, which applied for optimal reactive power is evaluated on an IEEE 30-bus power system. The modeling of reactive power optimization is established taking the minimum network losses as the objective. The simulation results and the comparison results with various optimization algorithms demonstrated that the MAFSA converges to better solutions than other approaches and the algorithm can make effectively use in reactive power optimization. Simultaneously, the validity and superiority of MAFSA was proved.

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